A. Bigano °, F. Bosello* , R. Roson’, R.S.J. Tol”

1. Economy Wide Impacts of Climate Change: A Joint Analysis for Sea Level Rise and Tourism A. Bigano °, F. Bosello* , R. Roson’, R.S.J. Tol” Chronic Risk of Global Climate Change to Urban Coasts and Economies Stevens Institute of Technology, NJ, 15-16 November 2007 °Fondazione Eni Enrico Mattei *Università di Milano e Fondazione Eni Enrico Mattei ’Università di Venezia e Fondazione Eni Enrico Mattei ”Free University of Amsterdam, Hamburg University, Carnegie Mellon University, ESRI Dublin

2. Introduction: future temperature + SLR IPCC FAR (2007)

3. Introduction: impacts IPCC FAR (2007)

4. Objectives Evaluate economically climate change impacts with a general equilibrium perspective (first and higher order welfare costs  substitution mechanisms + market interdependencies  changes induced by changes in relative prices) Initially one category of impact at a time Then jointly (this study tourism + SLR) Calibrate a climate change damage function accounting for “autonomous economic adaptation” Use and development of a CGE model/approach

5. Objectives This approach is innovative The predominant approach in climate change impact assessment is that of “direct costing”  Partial equilibrium: Damage = (“price”) x (“quantity”) This method is usually applied in “SLR studies” see e.g. Nichols et al. (2007) for discussion -> but also in other domains (e.g. health, agriculture etc.) and to calibrate cc damage functions in global studies (see e.g. Nordhaus (1995, 1999), Manne and Richels (1995, 2004), Tol (1995 – 2002)) This disregards rebounds and feedback: social economic systems adapt and “shocks” propagate

6. Sketching a CGE model Consumers (households, government) Maximise welfare from consumption demand supply Demand and supply functions “mimic” observed economic systems: parameters are calibrated on “real” data. All markets are Interdependent. Constrained by income Income Output marketsGoods and services Input markets K, L, Land, NR Constrained by technology Income demand supply Minimise cost of production Producers (firms, government)

7. The CGE Model GTAP-EF (Extended Version of GTAP-E Burniaux and Truong 2002) 16 Regions: USA: United States CAN: Canada WEU: Western Europe JPK: Japan and Korea ANZ: Australia New Zealand EEU: Eastern Europe FSU: Former Soviet Union MDE: China and India CAM: Rest of the World SAM: South America SAS: South Asia SEA: South East Asia CHI: China NAF: North Africa SSA: Sub-Saharan Africa SIS: Small Island States 17 Sectors: Rice Wheat Cereal Crops Vegetable Fruits Animals Forestry Fishing Coal Oil Gas Oil Products Electricity Water Energy Intensive industries Other industries Market Services Non-Market Services Calibrated in 1997

8. The CGE Model: consumption “tree” Using Income (from endowment ownrship) in fixed (C-D) shares for: Households max. Armington

9. The CGE Model: production “tree” Min. production cost Leontieff CES Armington CES CES Armington CES CES Armington

10. The CGE Model Investment • Redistribution mechanism based on the equalization of regional return to capital. • Households save a constant • share of their income. REG. 1 REG. 1 D “World Bank” A REG. 2 REG. 2 E B …….. …….. C REG. n F REG. n 1) Investment is Endogenous. 2) A,B,C flows ≠ D,E,F flows. 3) A region can run a foreign debt or credit.

11. “Benchmarking” the model in the future Starting point: core model calibrated in 1997. Necessary to get a future reference case “without climate change”(“Pseudo-calibration” ) This refers to obtaining a picture of the future world economy. In practice, long-run estimates of primary inputs (land, labour, capital and natural resources) stocks and productivity used to: Shock the model 1997 calibration equilibrium to obtain future benchmark equilibria ( 2050).

12. Data sources for the benchmark - Population: World Bank. - Capital stock:G-Cubed modelVersion48E (McKibbin, 2001). - Labour stock:G-Cubed modelVersion48E (McKibbin, 2001). - Labour productivity:G-Cubed model Version48E (McKibbin, 2001). - Crops’ productivity: IMAGE 2.2, B1 Scenario (RIVM, 2001).

13. Benchmark Assumptions % changes 1997-2050

14. Baseline GDP % changes 1997-2050

15. The Modeling Exercise SLR (No protection): Land loss is modeled as a negative “supply-side” shock on the endowment LAND (which is an exogenous variable in the model). Tourism: Changes in tourism demand are modeled as changes in the demand for recreational services (within the market service sector), income flows determined by additional foreign expenditure are modelled.

16. Climate Change Scenarios and Models • T = + 1.2 °C. in 2050 wrt 1980 -1999 • SLR= + 25 cm. in 2050 Environmental Impact Models Tourism -- > HTM model (Tol et al. 2002): changes in arrival, departures and expenditures, determined by socio-economic + environmental drivers (changes in temperature and coastal land availability) SLR -- > Data set on land loss wrt different sea-level rise scenarios (based on Delft Hydraulics GVA (1993), Beniston (1998 ), Nicholls (1995), Bijlsma et al. (1996))

17. Sea level rise alone Reference Year 2050: % changes wrt baseline Inputs to the CGE model Outputs from the CGE model

18. The difference between direct and general equilibrium cost

19. Tourism Alone Reference Year 2050: % changes wrt baseline

20. Tourism and sea level jointly

21. Conclusions Using a CGE approach to evaluate climate change impacts is important: huge difference respect to a partial equilibrium assessment Interactions among impacts are alslo non-negligible • A lot to do: • improve the quality of input data • expand the set of impacts considered (on health, energy demand, physical capital, agriculture etc.) • consider a dynamic setting

22. Thank You!